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Performance Verification for Behavior-Based Robot Missions
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DOI：10.1109/TRO.2015.2418592.png)
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Abstract
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Certain robot missions need to perform predictably in a physical environment that may have significant uncertainty. One approach is to leverage automatic software verification techniques to establish a performance guarantee. The addition of an environment model and uncertainty in both program and environment, however, means that the state space of a model-checking solution to the problem can be prohibitively large. An approach based on behavior-based controllers in a process-algebra framework that avoids state-space combinatorics is presented here. In this approach, verification of the robot program in the uncertain environment is reduced to a filtering problem for a Bayesian network. Validation results are presented for the verification of a multiple-waypoint and an autonomous exploration robot mission.
Keywords:
Autonomous agents
behavior-based systems
control architectures and programming
program verification
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